Discovery of Protein-Protein Interactions Using a Combination of Liguistic, Statistical and Graphical Information

The rapid publication of important research in the biomedical literature makes it increasingly difficult for researchers to keep current with significant work in their area of interest.

This paper reports a scalable method for the discovery of protein-protein interactions in Medline abstracts, using a combination of text analytics, statistical and graphical analysis, and a set of easily implemented rules. Applying these techniques to 12,300 abstracts, a precision of 0.61 and a recall of 0.90 were obtained, (f = 0.72) and when allowing for two-hop and three-hop relations discovered by graphical analysis, the precision can be as high as 0.81.

This combination of linguistic and statistical approaches appears to provide the highest precision and recall thus far reported in detecting protein-protein relations using text analytic approaches.

By: James W. Cooper; Aaron Kershenbaum

Published in: BMC Bioinformatics, volume 6, (no ), pages Art. no. 143 in 2005

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